Systems and methods for controlling secure persistent electronic communication account servicing with an intelligent assistant

ABSTRACT

The disclosed technology includes systems and methods for controlling enrollment and secure persistent SMS texting account servicing communications. A method is provided that includes receiving, at an enrollment web portal, enrollment data including: enrollment credentials identifying a user for authentication, a phone number of a mobile device associated with the user, and consent by the user to persistently interact with an account servicing system via SMS texting. The method includes: processing the received enrollment data, authenticating the user responsive to processing the received enrollment data, storing the phone number of the mobile device associated with the user in a phone number data storage, and generating, responsive to the authenticating, a revocable token for persistent access to a natural dialogue module via a SMS texting gateway for the mobile device identified by the phone number.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation application under 35 U.S.C. § 120 ofU.S. patent application Ser. No. 17/030,002, filed 23 Sep. 2020, whichissues as U.S. Pat. No. 10,986,047 on 20 Apr. 2021, which is acontinuation of U.S. patent application Ser. No. 16/740,678, filed 13Jan. 2020, which issued as U.S. Pat. No. 10,791,068 on 29 Sep. 2020,which is a continuation of U.S. patent application Ser. No. 16/516,862,filed 19 Jul. 2019, which is a continuation of U.S. patent applicationSer. No. 16/281,720, filed 21 Feb. 2019, which issued as U.S. Pat. No.10,374,983 on 6 Aug. 2019, which is a continuation of U.S. patentapplication Ser. No. 16/026,198, filed 3 Jul. 2018, and issued as U.S.Pat. No. 10,257,124 on 9 Apr. 2019, which is a continuation of U.S.patent application Ser. No. 15/916,521, filed 9 Mar. 2018 and issued asU.S. Pat. No. 10,044,647 on 7 Aug. 2018, the contents of which arehereby incorporated by reference in their entirety as if fully set forthherein. This application is also related to U.S. Pat. No. 10,200,314,which issued 5 Feb. 2019.

FIELD OF INVENTION

The present disclosure relates to systems and methods for providingaccount servicing with an intelligent assistant via SMS texting and,more particularly, to controlling enrollment and account servicingaccess using persistent authorization across multiple SMS communicationsessions.

BACKGROUND

Organizations that offer products and/or services associated withcustomer accounts have traditionally relied on customer servicerepresentatives to interact with customers for account servicing. Callcenters staffed with human representatives can provide certainadvantages, particularly for customers who wish to speak to a human.However, such staffing can be cost-prohibitive. To reduce cost andincrease account servicing efficiency, many organizations useinteractive voice response (IVR) systems or programs that generateautomatic written, auditory, or video responses via web and/or mobiledevice application channels. Such systems can provide customers withrequested information and perform routine account actions without havingto maintain a large workforce of customer service agents. While costeffective, existing computerized customer interaction systems tend toprovide an impersonal and robotic user experience, limited by scriptedquestions and responses, and can require a cumbersome authorizationprocess for each customer-service session.

Accordingly, there is a need for improved systems and methods to provideefficient and cost-effective customer interaction systems for accountservicing. Embodiments of the present disclosure are directed to thisand other considerations.

SUMMARY

Disclosed embodiments provide systems and methods for controllingenrollment and secure persistent SMS texting account servicingcommunications. A system is provided that includes one or moreprocessors in communication with: an enrollment web portal, a naturallanguage dialogue module, a SMS texting gateway, a phone number datastorage, and a token storage. The system includes memory incommunication with the one or more processors and storing instructionsthat, when executed by the one or more processors, are configured tocause the system to receive, at the enrollment web portal, enrollmentdata. The enrollment data includes: enrollment credentials identifying auser for authentication, a phone number of a mobile device associatedwith the user, and consent by the user to persistently interact with thesystem via SMS. The one or more processors of the system are furtherconfigured to authenticate the user responsive to processing thereceived enrollment data, store, in the phone number data storage, thephone number, and generate, responsive to the authentication, arevocable token for persistent access to the natural dialogue module viathe SMS texting gateway for a mobile device identified by the phonenumber. The one or more processors are further configured to initiate,responsive to the authentication, a persistent SMS texting session withthe mobile device identified by the phone number.

Consistent with the disclosed embodiments, methods for controllingenrollment and secure persistent SMS texting account servicingcommunications are also disclosed. Further features of the discloseddesign, and the advantages offered thereby, are explained in greaterdetail hereinafter with reference to specific embodiments illustrated inthe accompanying drawings, wherein like elements are indicated with likereference designators.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and which are incorporated into andconstitute a portion of this disclosure, illustrate variousimplementations and aspects of the disclosed technology and, togetherwith the description, serve to explain the principles of the disclosedtechnology.

FIG. 1 is an example block diagram representing a system 100 that may beused for controlling enrollment and secure persistent SMS textingaccount servicing communications.

FIG. 2 is a component diagram 200 of an example dialogue managementdevice.

FIG. 3 is an example intelligent assistant system functionality diagram300 for providing automated natural language dialogue for accountservicing via SMS texting.

FIG. 4 is an example system functionality diagram of a process 400 forcontrolling enrollment and secure persistent account servicingcommunications via SMS texting.

FIG. 5 is a flowchart of a method 500 for enrollment and securepersistent SMS texting account servicing communications.

DETAILED DESCRIPTION

Some implementations of the disclosed technology will be described morefully with reference to the accompanying drawings. This disclosedtechnology may, however, be embodied in many different forms and shouldnot be construed as limited to the implementations set forth herein. Thecomponents described hereinafter as making up various elements of thedisclosed technology are intended to be illustrative and notrestrictive. Many suitable components that would perform the same orsimilar functions as components described herein are intended to beembraced within the scope of the disclosed electronic devices andmethods. Such other components not described herein may include, but arenot limited to, for example, components developed after development ofthe disclosed technology.

It is also to be understood that the mention of one or more method stepsdoes not preclude the presence of additional method steps or interveningmethod steps between those steps expressly identified. Similarly, it isalso to be understood that the mention of one or more components in adevice or system does not preclude the presence of additional componentsor intervening components between those components expressly identified.

The disclosed technology and embodiments include systems and methods forcontrolling enrollment and secure persistent SMS texting accountservicing communications. A system is provided that includes one or moreprocessors in communication with: an enrollment web portal, a naturallanguage dialogue module, a SMS texting gateway, a phone number datastorage, and a token storage. The system includes memory incommunication with the one or more processors and storing instructionsthat, when executed by the one or more processors, are configured tocause the system to receive, at the enrollment web portal, enrollmentdata. The enrollment data includes: enrollment credentials identifying auser for authentication, a phone number of a mobile device associatedwith the user, and consent by the user to persistently interact with thesystem via SMS. The one or more processors of the system are furtherconfigured to authenticate the user responsive to processing thereceived enrollment data, store, in the phone number data storage, thephone number, and generate, responsive to the authentication, arevocable token for persistent access to the natural dialogue module viathe SMS texting gateway for a mobile device identified by the phonenumber.

In certain example implementations, the one or more processors may befurther configured to initiate, responsive to the authentication, apersistent SMS texting session with the mobile device identified by thephone number.

In another embodiment, a computer-implemented method is provided thatincludes receiving, at an enrollment web portal, enrollment dataincluding: enrollment credentials identifying a user for authentication,a phone number of a mobile device associated with the user, and consentby the user to persistently interact with an account servicing systemvia SMS texting. The method includes: processing the received enrollmentdata, authenticating the user responsive to processing the receivedenrollment data, storing the phone number of the mobile deviceassociated with the user in a phone number data storage, and generating,responsive to the authenticating, a revocable token for persistentaccess to a natural dialogue module via a SMS texting gateway for themobile device identified by the phone number. Certain exampleimplementations of the disclosed technology may include storing, in thephone number data storage, consent to communicate with the accountprovider via SMS text.

Certain example implementations of the disclosed technology may furtherinclude initiating a persistent SMS texting session with the mobiledevice identified by the phone number and based on the revocable token.

In another embodiment, a non-transitory computer readable storage mediumstoring instructions is provided for use with one or more processors incommunication with: an enrollment web portal, a natural languagedialogue module, a SMS texting gateway, a phone number data storage, atoken storage, and memory. The instructions are configured to cause theone or more processors to perform a method that includes: receiving, atthe enrollment web portal, enrollment data including: enrollmentcredentials identifying a user for authentication, a phone number of amobile device associated with the user, and consent by the user topersistently interact with an account servicing system via the SMStexting gateway. The instructions are further configured to cause theone or more processors to perform the method that includes processingthe received enrollment data, authenticating the user responsive toprocessing the received enrollment data, storing the phone number of themobile device associated with the user in the phone number data storage,generating, responsive to the authenticating, a revocable token forpersistent access to a natural dialogue module via a SMS texting gatewayfor the mobile device identified by the phone number, and storing therevocable token in the token storage.

Certain example implementations of the disclosed technology utilize anatural language intelligent assistant for performing account servicingfunctions via SMS texting. Contact may be initiated with the intelligentassistant just as any other SMS recipient. For example, the intelligentassistant may include an identifier accessible from a list of contactson a customer device with which an SMS conversation may be initiated.Certain example implementations can help address and overcomeinefficiencies and security issues associated with conventional accountservicing systems. For example, embodiments disclosed herein enablecustomers to access account information and/or perform account servicingfunctions by texting with the intelligent assistant—without having tologin to a website or mobile app every time. Certain exampleimplementations of the disclosed technology may provide an improvedexperience for a customer, by enabling account servicing through digitalself-service channels without the friction of a customer having tonavigate to a website or mobile app and/or provide login credentialseach time there is an interaction with the system.

In an example implementation, customers may establish persistent secureaccess to account servicing via SMS text based on an initial (one-time)login and authentication process. In certain example implementations ofthe disclosed technology, a customer may perform the initial login tothe website or mobile app by supplying authentication credentials (suchas a code, two-factor authorization, biometric information, etc.). Onceauthenticated, a customer may be granted persistent SMS access byproviding additional information, including (but not limited to) theirmobile phone number, consent to communicate with the account providervia SMS text, and consent to service their account via SMS text.According to an example implementation of the disclosed technology, auser may revoke their consent to communicate with the account providervia SMS text, which may update the phone number status in a phone numberdata store (as will be discussed further with reference to FIGS. 1 and4). In certain implementations, when the customer revokes consent, suchaction may cause the token in an enrollment token store to expire thenext time the customer attempts to access the system via SMS text and/orwhen the phone number status is checked in the phone number data store.In certain example implementations, if the token has been revoked, or ifit expires, the system may direct the customer back to the website ormobile app, to authenticate and provide consent to service their accountvia SMS text.

Certain example implementations of the disclosed technology provide asecure and persistent authentication process for accessing accountservicing functions via SMS texting by utilizing a revocable token,which may be utilized to secure and protect access to sensitiveinformation. For example, the mobile phone number and the consent tocommunicate with the account provider via SMS text may be persisted in adata store, which can only be changed while the customer is logged in.In certain example implementations, the revocable token may be based onthe association of the customer's mobile phone number with their digitalprofile identification. In an example implementation, each time acustomer interacts with the intelligent assistant via SMS text, thesystem checks the data store to verify that the customer still has thesame mobile phone number and has not revoked consent to communicate viaSMS text. The token is also checked to see if it is still valid. If therevocable token has expired, customers must log in to the website ormobile app again to re-establish the persistent authentication token foraccount servicing via SMS text. According to an example implementationof the disclosed technology, the revocable token is distinguished from atypical “one-time” token in that the revocable token may persistindefinitely until it is revoked (by the customer or based on a policy)or it may persist for a duration (for example, 60 days, 120 days,months, etc.) until it is revoked or until it expires.

In accordance with certain example implementations of the disclosedtechnology, the token may expire when any of the following occurs: thecustomer changes their mobile number; the customer revokes consent tocommunicate via SMS text; the customer revokes consent to service theiraccount via SMS text; the customer does not service their account viaSMS text for a pre-determined number of days; and/or the customer'smobile number appears on a list of mobile numbers that have switchedcarriers, as well as any other determination that the customer's mobiledevice has been compromised or may no longer be considered a trusteddevice. In accordance with certain example implementations of thedisclosed technology, a mobile number that has been assigned to a newcarrier may be detected by an automated process that checks thecustomer's mobile number against mobile number feed provided by wirelesscarriers.

Reference will now be made in detail to example embodiments of thedisclosed technology, examples of which are illustrated in theaccompanying figures and disclosed herein. Wherever convenient, the samereferences numbers will be used throughout the drawings to refer to thesame or like parts.

FIG. 1 is an example block diagram representing a system 100 that may beused for controlling enrollment and secure persistent SMS textingaccount servicing communications, according to an example implementationof the disclosed technology. System 100 may be provided or controlled byan account provider organization, a non-limiting example including afinancial service provider. The account servicing may be facilitated bythe dialog management device 122 and/or the natural language processing(NLP) device 124 of the system, as will be further explained. In certainexample implementations, the system 100 may be configured to perform oneor more of: authentication, enrollment in SMS account servicing, tokencontrol, and account servicing. The system 100 utilizes automatednatural language dialogue that may adaptively respond to customermessages based on an evolving customer context associated with a givencustomer. The components and arrangements shown in FIG. 1 are notintended to limit the disclosed embodiments as the components used toimplement the disclosed processes and features may vary.

As shown in FIG. 1, the system 100 may be utilized to communicate with auser device 102 via various paths, such as through a SMS aggregator 104(or gateway), which may serve as an intermediary between mobile serviceproviders 106 and the system 100. In certain example implementations,the SMS aggregator 104 and/or the user device 102 may be incommunication with the system 100 via a network 108, including, but notlimited to the Internet. Certain example implementations of thedisclosed technology can include a local area network 114 forcommunication with the various modules of the system.

In certain example implementations, the system can include an APIgateway 110 to act as a “front door” for applications access data,logic, and/or functionality from the API server 126 and/or otherback-end services. In certain example implementations, the API gateway110 may be configured to handle tasks involved in accepting andprocessing concurrent API calls, including traffic management,authorization, access control, monitoring, API version management, etc.

In accordance with certain example implementations of the disclosedtechnology, the system 100 may be operated by an account provider andmay include one or more of: a phone number authentication module 116, anenrollment token store 118, a phone number data store 120, a dialoguemanagement device 122, a natural language processing (NLP) device 124,memory 128 (which may house one or more databases), and one or more webservers 130. As shown, the various modules 110-130 may be incommunication via the local network 114. In accordance with certainexample implementations of the disclosed technology, the phone numberauthentication module 116 may be utilized to receive and/or parse and/ordecode an incoming SMS message to extract the sender's phone number. Forexample, the SMS message may arrive at the system 100 in the form of aSMS protocol description unit (PDU) string that can include encodedinformation identifying the number to which the message is to be sent,the sender's phone number, the SMS message, and other identifiers. Incertain example implementations, the phone number authentication module116 may extract and decode (or receive) the (extracted/decoded) sender'sphone number and may access the phone number data store 120 to determineif the extracted phone number matches with any of the phone numberstored in the phone number data store 120. In certain exampleimplementations, the phone number data store 120 may take the form of asearchable database and/or a look-up table that stores phone numbers forcustomers of the account provider. In one example implementation of thedisclosed technology, the phone number data store 120 may store mobilephone numbers for authenticated, consenting customers who are currentlyenrolled in the account servicing via SMS messages. In certain exampleimplementations, the phone number data store 120 may include fields withall known phone numbers of existing customers, and one or more fieldsassociated with each phone number that may indicate a status of thephone number. In this implementation, the phone number authenticationmodule 116 may read both fields and authenticate the sender's mobilephone number if there is a corresponding matching phone number in thephone number data store 120, and if the status field indicates that thenumber is associated with an authenticated and consenting customer. Inaccordance with certain example implementations of the disclosedtechnology, the enrollment token store 118 may take the form of asearchable database and/or a look-up table (similar to the phone numberdata store 120) that stores uniquely identifiable revocable tokens forcustomers of the account provider. In one example implementation of thedisclosed technology, the enrollment token store 118 may store tokensfor authenticated, consenting customers who are currently enrolled inthe account servicing via SMS messages. In certain exampleimplementations, the enrollment token store 118 may include fields withaccount identifiers for existing customers and/or one or more fieldsindicating a status of the associated revocable tokens (i.e., forauthenticated and consenting customers, or otherwise). In certainexample implementations, the phone number authentication module 116 mayread one or more fields in the enrollment token store 118 to determinethe status of the associated revocable token. Additional descriptions ofthese and related processes involving the modules 110-130 will beexplained further with reference to FIGS. 2-4.

In some embodiments, a customer may operate user device 102. User device102 can include one or more of a mobile device, smart phone, generalpurpose computer, tablet computer, laptop computer, smart wearabledevice, voice command device, other mobile computing device, or anyother device capable of communicating via SMS with the service provider106 and/or the network 108, and ultimately communicating with one ormore components of the system 100.

According to an example implementation of the disclosed technology, theuser device 102 may belong to or be provided by a customer, or may beborrowed, rented, or shared. Customers may include individuals such as,for example, subscribers, clients, prospective clients, or customers ofan entity associated with an organization, such as individuals who haveobtained, will obtain, or may obtain a product, service, or consultationfrom an entity associated with the organization. According to someembodiments, the user device 102 may include an environmental sensor forobtaining audio or visual data, such as a microphone and/or digitalcamera, a geographic location sensor for determining the location of thedevice, an input/output device such as a transceiver for sending andreceiving data, a display for displaying digital images, one or moreprocessors including a sentiment depiction processor, and a memory incommunication with the one or more processors.

According to an example implementation of the disclosed technology, thenetwork 108 may be of any suitable type, including individualconnections via the Internet such as cellular or WiFi networks. In someembodiments, network 108 may connect terminals, services, and mobiledevices using direct connections such as radio-frequency identification(RFID), near-field communication (NFC), Bluetooth™, low-energyBluetooth™ (BLE), WiFi™, ZigBee™, ambient backscatter communications(ABC) protocols, USB, WAN, or LAN. Because the information transmittedmay be personal or confidential, security concerns may dictate one ormore of these types of connections be encrypted or otherwise secured. Insome embodiments, however, the information being transmitted may be lesspersonal, and therefore the network connections may be selected forconvenience over security.

According to an example implementation of the disclosed technology, thenetwork 108 may include any type of computer networking arrangement usedto exchange data. For example, the network 108 may be the Internet, aprivate data network, virtual private network using a public network,and/or other suitable connection(s) that enables components in thesystem 100 to send and receive information between the components of thesystem 100. In certain example implementations, the network 108 may alsoinclude a public switched telephone network (“PSTN”) and/or a wirelessnetwork.

In accordance with certain example implementations of the disclosedtechnology, the system 100 may be associated with and optionallycontrolled by an entity such as a business, corporation, individual,partnership, or any other entity that provides one or more of goods,services, and consultations to individuals such as customers. The system100 can include or be in contact with one or more servers and computersystems for performing one or more functions associated with productsand/or services that an organization provides. Such servers and computersystems may include, for example, web servers, call center servers,and/or transaction servers, as well as any other computer systemsnecessary to accomplish tasks associated with the organization and/orthe needs of customers (which may be customers of the entity associatedwith the organization). In an example implementation, the system mayinclude a web server 130 configured to generate and provide one or morewebsites accessible to customers, as well as any other individualsinvolved in the organization normal operations.

According to an example implementation of the disclosed technology, theweb server 130 may include a computer system configured to receivecommunications from a user device 102 via for example, a mobileapplication, a chat program, an instant messaging program, avoice-to-text program, an SMS message, email, or any other type orformat of written or electronic communication. The web server 130 mayinclude one or more processors and one or more web server databases,which may be any suitable repository of website data. Information storedin web server 130 may be accessed (e.g., retrieved, updated, and addedto) via the local network 114 and/or the network 108 by one or moredevices (e.g., dialogue management device 122) of the system 100. Insome embodiments, one or more processors may be used to implement anautomated natural language dialogue system that may interact with acustomer via different types of communication channels such as awebsite, mobile application, instant messaging application, SMS message,email, or any other type of electronic communication. In certain exampleimplementations, when an incoming message is received from a user device102, the web server 130 may be configured to determine the type ofcommunication channel user device 102 used to generate the incomingmessage.

Certain example implementations of the system 100 may also include oneor more call center servers (not shown) that may include a computersystem configured to receive, process, and route telephone calls andother electronic communications between a customer operating user device102 and the dialogue management device 122. Information stored in callcenter server, for example may be accessed (e.g., retrieved, updated,and added to) via local network 114 and/or the network 105 by one ormore devices (e.g., dialogue management device 122) of system 100. Insome embodiments, one or more processors may be used to implement aninteractive voice response (IVR) system that interacts with the customerover the phone.

Certain example implementations of the system 100 may also include oneor more transaction servers (not shown) that may include a computersystem configured to process one or more transactions involving anaccount associated with customers, or a request received from customers.In some embodiments, transactions can include, for example, aproduct/service purchase, product/service return, financial transfer,financial deposit, financial withdrawal, financial credit, financialdebit, dispute request, warranty coverage request, and any other type oftransaction associated with the products and/or services that an entityassociated with the organization provides to individuals such ascustomers. The transaction server, for example, may have one or moreprocessors and one or more transaction server database, which may be anysuitable repository of transaction data. Information stored intransaction server may be accessed (e.g., retrieved, updated, and addedto) via local network 114 and/or network 108 by one or more devices(e.g., dialogue management device 122) of system 100.

In some embodiments, a transaction server may track and store event dataregarding interactions between a third party and the organization onbehalf of the customer. For example, third party interactions may betracked, which can include purchase requests, refund requests, warrantyclaims, account withdrawals and deposits, and any other type ofinteraction that a third-party server may conduct with the organizationon behalf of an individual such as customer.

In accordance with certain example implementations of the disclosedtechnology, the local network 114 may include any type of computernetworking arrangement used to exchange data in a localized area, suchas WiFi, Bluetooth™ Ethernet, and other suitable network connectionsthat enable components of the organization to interact with one anotherand to connect to the network 108 for interacting with components of thesystem 100. In some embodiments, the local network 114 can include aninterface for communicating with or linking to the network 108. In otherembodiments, components of an organization may communicate via thenetwork 108, without a separate local network 114.

In accordance with certain example implementations of the disclosedtechnology, and with continued reference to FIG. 1, the dialoguemanagement device 122 can include one or more computer systemsconfigured to compile data from a plurality of sources, such as the webserver 130, a call center server, and/or a transaction server. Incertain example implementations, the dialogue management device 122 maybe utilized to correlate compiled data, analyze the compiled data,arrange the compiled data, generate derived data based on the compileddata, and store the compiled and derived data in a database such asdatabase 128. According to some embodiments, database 128 may beassociated with an organization and/or its related entity and may storea variety of information relating to customers, transactions, andbusiness operations. In certain example implementations, the database128 may also serve as a back-up storage device. In certain exampleimplementations, the database 128 may be accessed by dialogue managementdevice 122 and may be used to store records of every interaction,communication, and/or transaction a particular customer has had with thesystem 100 and/or its related entity in the past, for example, to enablethe creation of an ever-evolving customer context that may enabledialogue management device 122 to provide customized and adaptivedialogue when interacting with the customer.

In accordance with certain example implementations of the disclosedtechnology, the API server 126 may include a computer system configuredto execute one or more application program interfaces (APIs) thatprovide various functionalities related to the operations of the system100. In some embodiments, API server 126 may include API adapters thatenable the API server 126 to interface with and utilize enterprise APIsmaintained by the system 100 and/or an associated API's that may behoused on other systems or devices. In some embodiments, APIs canprovide functions that include, for example, retrieving customer accountinformation, modifying customer account information, executing atransaction related to an account, scheduling a payment, authenticatinga customer, updating a customer account to opt-in or opt-out ofnotifications, and any other such function related to management ofcustomer profiles and accounts. In certain example implementations, theAPI server 126 may include one or more processors and/or one or more APIdatabases, which may be any suitable repository of API data. In certainexample implementations, information stored in the API server 126 may beaccessed (e.g., retrieved, updated, and added to) via local network 114and/or network 108 by one or more devices (e.g., dialogue managementdevice 122) of the system 100. In some embodiments, an API processor maybe used to implement one or more APIs that can access, modify, andretrieve customer account information. In certain embodiments, real-timeAPIs consistent with certain disclosed embodiments may useRepresentational State Transfer (REST) style architecture, and in thisscenario, the real time API may be called a RESTful API.

In certain embodiments, a real-time API may include a set of HypertextTransfer Protocol (HTTP) request messages and a definition of thestructure of response messages. In certain aspects, the API may allow asoftware application, which is written against the API and installed ona client (such as, for example, a transaction server) to exchange datawith a server that implements the API (such as, for example, API server126), in a request-response pattern. In certain embodiments, therequest-response pattern defined by the API may be configured in asynchronous fashion and require that the response be provided inreal-time. In some embodiments, a response message from the server tothe client through the API consistent with the disclosed embodiments maybe in the format including, for example, Extensible Markup Language(XML), JavaScript Object Notation (JSON), and/or the like.

In some embodiments, the API design may also designate specific requestmethods for a client to access the server. For example, the client maysend GET and POST requests with parameters URL-encoded (GET) in thequery string or form-encoded (POST) in the body (e.g., a formsubmission). Additionally, or alternatively, the client may send GET andPOST requests with JSON serialized parameters in the body. Preferably,the requests with JSON serialized parameters use “application/j son”content-type. In another aspect, an API design may also require theserver implementing the API return messages in JSON format in responseto the request calls from the client.

With continued reference to FIG. 1, the system 100 may include a naturallanguage processing device (NLP device) 124, which may include acomputer system configured to receive and process incoming dialoguemessages and determine a meaning of the incoming dialogue message. Forexample, the NLP device 124 may be configured to receive and execute acommand containing an incoming dialogue message where the commandinstructs the NLP device 124 to determine the meaning of the incomingdialogue message. The NLP device 124 may be configured to continuouslyor intermittently listen for and receive commands from a command queueto determine if there are any new commands directed to the NLP device124. Upon receiving and processing an incoming dialogue message, the NLPdevice 124 may output the meaning of an incoming dialogue message in aformat that other devices can process. For example, the NLP device 124may receive an incoming dialogue message stating “Hello, I would like toknow my account balance please,” and may determine that this statementrepresents a request for an account balance. In certain exampleimplementations, the NLP device 124 may be configured to output an eventrepresenting the meaning of the incoming dialogue message to an eventqueue for processing by another device. In some embodiments, the NLPdevice 124 may be configured to generate a natural language phrase inresponse to receiving a command. Accordingly, in some embodiments, theNLP device 124 may be configured to output an event that contains datarepresenting natural language dialogue.

In accordance with certain example implementations of the disclosedtechnology, the NLP device 124 may include one or more processors andone or more NLP databases, which may be any suitable repository of NLPdata. Information stored in the NLP device 124 may be accessed (e.g.,retrieved, updated, and added to) via local network 114 and/or network108 by one or more devices (e.g., the dialogue management device 122) ofthe system 100. In some embodiments, an NLP processor may be used toimplement an NLP system that can determine the meaning behind a stringof text and convert it to a form that can be understood by otherdevices.

Although the preceding description describes various functions of a webserver 130, call center server, transaction server, dialogue managementdevice 122, database 128, an API server 126, and a natural languageprocessing (NLP) device 124, in some embodiments, some or all of thesefunctions may be carried out by a single computing device.

The features and other aspects and principles of the disclosedembodiments may be implemented in various environments specificallyconstructed for performing the various processes and operations of thedisclosed embodiments or they may include a general-purpose computer orcomputing platform selectively activated or reconfigured by program codeto provide the necessary functionality. Further, the processes disclosedherein may be implemented by a suitable combination of hardware,software, and/or firmware. For example, certain disclosed embodimentsmay be implemented by general purpose machines configured to executespecial software programs that perform processes consistent with thedisclosed embodiments. Alternatively, the disclosed embodiments mayimplement a specialized apparatus or system configured to executesoftware programs that perform processes consistent with the disclosedembodiments. Furthermore, although some disclosed embodiments may beimplemented by general purpose machines as computer processinginstructions, all or a portion of the functionality of the disclosedembodiments may be implemented instead in dedicated electronicshardware.

The disclosed embodiments also relate to tangible and non-transitorycomputer readable media that include program instructions or programcode that, when executed by one or more processors, perform one or morecomputer-implemented operations. The program instructions or programcode may include specially designed and constructed instructions orcode, and/or instructions and code well-known and available to thosehaving ordinary skill in the computer software arts. For example, thedisclosed embodiments may execute high level and/or low-level softwareinstructions, such as machine code (e.g., such as that produced by acompiler) and/or high-level code that can be executed by a processorusing an interpreter.

FIG. 2 is a component diagram 200 depicting additional details of theexample dialogue management device 122 (as shown in FIG. 1). In certainexample implementations, one or more of the modules or components110-130 as shown and discussed above with reference to FIG. 1 (forexample, the phone number authentication module 116, the enrollmenttoken store 118, the phone number data store 120, the natural languageprocessing (NLP) device 124, the database 128, and one or more webservers 130) may be configured similarly as described with respect todialogue management device 122. As shown in FIG. 2, dialogue managementdevice 122 may include a processor 210, an input/output (“I/O”) device220, a memory 230 containing an operating system (“OS”) 240 and aprogram 250. For example, dialogue management device 122 may be a singleserver or may be configured as a distributed computer system includingmultiple servers or computers that interoperate to perform one or moreof the processes and functionalities associated with the disclosedembodiments. In some embodiments, the dialogue management device 122 mayfurther include a peripheral interface, a transceiver, a mobile networkinterface in communication with the processor 210, a bus configured tofacilitate communication between the various components of the dialoguemanagement device 122, and a power source configured to power one ormore components of the dialogue management device 122.

A peripheral interface may include the hardware, firmware and/orsoftware that enables communication with various peripheral devices,such as media drives (e.g., magnetic disk, solid state, or optical diskdrives), other processing devices, or any other input source used inconnection with the instant techniques. In some embodiments, aperipheral interface may include a serial port, a parallel port, ageneral purpose input and output (GPIO) port, a game port, a universalserial bus (USB), a micro-USB port, a high definition multimedia (HDMI)port, a video port, an audio port, a Bluetooth™ port, a near-fieldcommunication (NFC) port, another like communication interface, or anycombination thereof.

In some embodiments, a transceiver may be configured to communicate withcompatible devices and ID tags when they are within a predeterminedrange. A transceiver may be compatible with one or more of:radio-frequency identification (RFID), near-field communication (NFC),Bluetooth™, low-energy Bluetooth™ (BLE), WiFi™, ZigBee™, ambientbackscatter communications (ABC) protocols or similar technologies.

A mobile network interface may provide access to a cellular network, theInternet, or another wide-area or local area network. In someembodiments, a mobile network interface may include hardware, firmware,and/or software that allows the processor(s) 210 to communicate withother devices via wired or wireless networks, whether local or widearea, private or public, as known in the art. A power source may beconfigured to provide an appropriate alternating current (AC) or directcurrent (DC) to power components.

The processor 210, for example, may include one or more of amicroprocessor, microcontroller, digital signal processor, co-processoror the like or combinations thereof capable of executing storedinstructions and operating upon stored data. The memory 230, forexample, may include, in some implementations, one or more suitabletypes of memory (e.g. such as volatile or non-volatile memory, randomaccess memory (RAM), read only memory (ROM), programmable read-onlymemory (PROM), erasable programmable read-only memory (EPROM),electrically erasable programmable read-only memory (EEPROM), magneticdisks, optical disks, floppy disks, hard disks, removable cartridges,flash memory, a redundant array of independent disks (RAID), and thelike), for storing files including an operating system, applicationprograms (including, for example, a web browser application, a widget orgadget engine, and or other applications, as necessary), executableinstructions and data. In one embodiment, the processing techniquesdescribed herein are implemented as a combination of executableinstructions and data within the memory 230.

In certain example implementations, the processor 210 may be one or moreknown processing devices, such as, but not limited to, a microprocessorfrom the Pentium™ family manufactured by Intel™ or the Turion™ familymanufactured by AMD™. The processor 210 may constitute a single core ormultiple core processor that executes parallel processes simultaneously.For example, the processor 210 may be a single core processor that isconfigured with virtual processing technologies. In certain embodiments,the processor 210 may use logical processors to simultaneously executeand control multiple processes. The processor 210 may implement virtualmachine technologies, or other similar known technologies to provide theability to execute, control, run, manipulate, store, etc. multiplesoftware processes, applications, programs, etc. One of ordinary skillin the art would understand that other types of processor arrangementscould be implemented that provide for the capabilities disclosed herein.

According to an example implementation of the disclosed technology, thedialogue management device 122 may include one or more storage devicesconfigured to store information used by processor 210 (or othercomponents) to perform certain functions related to the disclosedembodiments. In one example the dialogue management device 122 mayinclude memory 230 that includes instructions to enable processor 210 toexecute one or more applications, such as server applications, networkcommunication processes, and any other type of application or softwareknown to be available on computer systems. Alternatively, theinstructions, application programs, etc. may be stored in an externalstorage or available from a memory over a network. The one or morestorage devices may be a volatile or non-volatile, magnetic,semiconductor, tape, optical, removable, non-removable, or other type ofstorage device or tangible computer-readable medium.

In one embodiment, dialogue management device 122 may include memory 230that includes instructions that, when executed by processor 210, performone or more processes consistent with the functionalities disclosedherein. Methods, systems, and articles of manufacture consistent withdisclosed embodiments are not limited to separate programs or computersconfigured to perform dedicated tasks. For example, dialogue managementdevice 122 may include memory 230 that may include one or more programs250 to perform one or more functions of the disclosed embodiments. Forexample, in some embodiments, dialogue management device 122 may includea rules-based platform (RBP) 290 for generating zero or more commands inresponse to processing an event, in accordance with a set of predefinedrules. In some embodiments, dialogue management device 122 may include atrained machine learning model (MLM) 295 for generating zero or morecommands in response to processing an event, in accordance with a modelthat may be continuously or intermittently updated. Moreover, theprocessor 210 may execute one or more programs 250 located remotely fromsystem 100. For example, system 100 may access one or more remoteprograms 250 (such as rules-based platform 290 or trained machinelearning model 295), that, when executed, perform functions related todisclosed embodiments.

The memory 230 may include one or more memory devices that store dataand instructions used to perform one or more features of the disclosedembodiments. The memory 230 may also include any combination of one ormore databases controlled by memory controller devices (e.g., server(s),etc.) or software, such as document management systems, Microsoft™ SQLdatabases, SharePoint™ databases, Oracle™ databases, Sybase™ databases,or other relational or non-relational databases. The memory 230 mayinclude software components that, when executed by processor 210,perform one or more processes consistent with the disclosed embodiments.In some embodiments, memory 230 may include a customer informationdatabase 280 for storing related data to enable dialogue managementdevice 122 to perform one or more of the processes and functionalitiesassociated with the disclosed embodiments. The customer informationdatabase 280 may include stored data relating to a customer profile andcustomer accounts, such as for example, customer identificationinformation (e.g., name, age, sex, birthday, address, VIP status, keycustomer status, preferences, preferred language, vehicle(s) owned,greeting name, channel, talking points (e.g., favorite sports team),etc.), bank accounts, mortgage loan accounts, car loan accounts, othersuch accounts, account numbers, authorized users associated with one ormore accounts, account balances, account payment history, and other suchtypical account information. The customer information database 280 mayfurther include stored data relating to previous interactions between anorganization (or its related entity) and a customer. For example, thecustomer information database 280 may store customer interaction datathat includes records of previous customer service interactions with acustomer via a website, SMS, a chat program, a mobile application, anIVR system, or notations taken after speaking with a customer serviceagent. The customer information database 280 may also includeinformation about business transactions between an organization (and/orits related entity) and a customer that may be obtained from, forexample, a transaction server. The customer information database 280 mayalso include customer feedback data such as an indication of whether anautomated interaction with a customer was successful, online surveysfilled out by a customer, surveys answered by a customer followingprevious interactions to the account provider, digital feedback providedthrough websites or mobile application associated with the organizationor its related entity (e.g., selecting a smiley face or thumbs up toindicate approval), reviews written by a customer, complaint formsfilled out by a customer, information obtained from verbal interactionswith customer (e.g., information derived from a transcript of a customerservice call with customer that is generated using, for example, voicerecognition techniques) or any other types of communications from acustomer to the organization or its related entity. According to someembodiments, the functions provided by the customer information database280 may also be provided by a database that is external to the dialoguemanagement device 122.

In accordance with certain example implementations of the disclosedtechnology, the memory 230 may also include an event queue 260 fortemporarily storing queued events and a command queue 270 fortemporarily storing queued commands. The processor 210 may receiveevents from the event queue 260 and in response to processing the eventusing the rules-based platform 290 and/or the trained machine learningmodel 295, generate zero or more commands to be output to the commandqueue 270. According to some embodiments, dialogue management device 122may place commands in the command queue 270 in the order they aregenerated. In certain example implementations of the disclosedtechnology, the command queue 270 may be monitored to detect commandsthat are designated to be executed by the monitoring device and mayaccess pertinent commands. The event queue 260 may receive events fromother devices. According to some embodiments, events may be placed inthe event queue 260 in a first-in first-out (FIFO) order, such thatevents may then processed by the dialogue management device 122 in theorder they are received or generated.

The dialogue management device 122 may also be communicatively connectedto one or more memory devices (e.g., databases) locally or through anetwork. The remote memory devices may be configured to storeinformation and may be accessed and/or managed by dialogue managementdevice 122. By way of example, the remote memory devices may be documentmanagement systems, Microsoft™ SQL database, SharePoint™ databases,Oracle™ databases, Sybase™ databases, or other relational ornon-relational databases. Systems and methods consistent with disclosedembodiments, however, are not limited to separate databases or even tothe use of a database.

The dialogue management device 122 may also include one or more I/Odevices 220 that may include one or more interfaces for receivingsignals or input from devices and providing signals or output to one ormore devices that allow data to be received and/or transmitted bydialogue management device 122. For example, dialogue management device122 may include interface components, which may provide interfaces toone or more input devices, such as one or more keyboards, mouse devices,touch screens, track pads, trackballs, scroll wheels, digital cameras,microphones, sensors, and the like, that enable dialogue managementdevice 122 to receive data from one or more users (such as, for example,via user device 102, as discussed with reference to FIG. 1).

In certain embodiments of the disclosed technology, the dialoguemanagement device 122 may include any number of hardware and/or softwareapplications that are executed to facilitate any of the operations. Theone or more I/O interfaces may be utilized to receive or collect dataand/or user instructions from a wide variety of input devices. Receiveddata may be processed by one or more computer processors as desired invarious implementations of the disclosed technology and/or stored in oneor more memory devices.

While dialogue management device 122 has been described as one form forimplementing the techniques described herein, those having ordinaryskill in the art will appreciate that other, functionally equivalenttechniques may be employed. For example, as known in the art, some orall of the functionality implemented via executable instructions mayalso be implemented using firmware and/or hardware devices such asapplication specific integrated circuits (ASICs), programmable logicarrays, state machines, etc. Furthermore, other implementations of thedialogue management device 122 may include a greater or lesser number ofcomponents than those illustrated.

FIG. 3 is an example intelligent assistant system functionality diagram300 for providing automated natural language dialogue for accountservicing via SMS texting. Certain processes discussed with respect toFIG. 3 (as discussed in detail below) may be executed by the system 100,as discussed above with respect to FIG. 1.

FIG. 4 is an example system functionality diagram of a process 400 forcontrolling enrollment and secure persistent account servicingcommunications via SMS texting. In some embodiments, the process 400 ofFIG. 4 may correspond to, and/or be implicit in the system functionalitydiagram 300 as shown in FIG. 3. For example, the process 400, asdepicted in FIG. 4 (and discussed in detail below) may be performed bythe dialogue management device 122 (with associated processor 210executing program instructions 250 in memory 230, as discussed abovewith reference to FIG. 2.) In some embodiments, certain portions of thefunctionality of the process 400 may be delegated, as appropriate, toother elements in the system 100 discussed with reference to FIG. 1.

With continued reference to FIG. 3, a first event may be placed in theevent queue 260 in response to receiving a customer dialogue message,for example, from the user device 102. According to certain exampleimplementations of the disclosed technology, a customer dialogue messagemay be sent using various communication mediums, such as for example,SMS, a voice-to-text device, a chat application, an instant messagingapplication, a mobile application, an IVR system, or any other suchmedium that may be sufficient to send and receive electroniccommunications. Responsive to the incoming customer dialog message, theevent may be generated by, for example, a RESTful API interfacing with areceiving device of the system 100.

In accordance with certain example implementations of the disclosedtechnology, after the event is created, it may be placed in the eventqueue 260. An event queue 260 may be configured to temporarily store aplurality of events. According to some embodiments, events are placed inthe event queue in a first-in first-out (FIFO) manner, such that theevents will be executed in the order that they were received. In someembodiments, the event queue 260 and/or the command queue 270 may bepart of the dialogue management device 122. In some embodiments, boththe event queue 260 and the command queue 270 may be present on a deviceor component other than dialogue management device 122. For example, insome embodiments, the event queue 260 and the command queue 270 may bemaintained on a cloud server that is accessible by the dialoguemanagement device 122, the API server 126, the NLP device 124, and/orthe communication interface 301. According to some embodiments, an eventmay represent different types of information such as, for example, textreceived from a customer, customer account information, or a request toperform some account-related action. For example, an event mightrepresent a user dialogue message that has been sent to system 100 viaSMS that read “Hello, can you please tell me my account balance?”According to some embodiments, an event may have certain metadata (suchas a phone number and/or token) associated with it that is sufficient toallow the system to determine the identity of a customer associated withthe event and/or a communication medium from which the even originated,as will be discussed below with reference to FIG. 4.

According to some embodiments, the dialogue management device 122 maycontinuously or intermittently monitor the event queue 260. In responseto detecting an event (e.g., the first event) in the event queue, theevent may be received at the dialogue management device 122 from theevent queue 260. In some embodiments, the dialogue management device 122may include a rules-based platform, a trained machine learning model,and a customer context. According to some embodiments, the customercontext may be derived from customer information associated with aparticular customer that is stored in the system 100. For example,customer information may be stored in the phone number data store 120,the enrollment token store 118, and/or the database 128 shown in FIG. 1,and/or the database 280 shown in FIG. 2. In some embodiments, thecustomer information may include one or more of account types, accountstatuses, phone number, token, transaction history, conversationhistory, people models, an estimate of customer sentiment, customergoals, and customer social media information. In accordance with certainexample implementations of the disclosed technology, the system 100 maybe configured to adapt and tailor its responses to a particular customerbased on the customer context and/or customer information. According tosome embodiments, the customer context may be updated each time thedialogue management device 122 receives a new event from the event queue260. For example, in some embodiments, the customer context may beupdated by the dialogue management device 122 responsive to receivingupdated customer information.

In certain example implementations, the dialogue management device 122may, in response to processing the first event, generate a first commandto be placed in a command queue 270. According to some embodiments, thedialogue management device 122 may generate a command based on theprocessed event, the customer context, and/or customer information usingone or more of a rules-based platform 290 and a trained machine learningmodel 295 as discussed with reference to FIG. 2. For example, in someuse cases a command may be generated using the rules-based platform 290,whereas in other use cases a command may be generated using the trainedmachine learning model 295, and further use cases may be handled by boththe rules-based platform 290 and the trained machine learning model 295working in concert. In some embodiments, the trained machine learningmodel 295 may be used as a way of enhancing the performance of therules-based platform 290 by, for example, determining which rules havepriority over other rules and what rules should be applied in a givencontext. According to some embodiments, the commands generated by thedialogue management device 122 in response to a particular event maychange as the customer context and/or customer information is updatedover time. Further, changes to the rules in the rules-based platform 290or further training of the machine learning model 295 may also result indifferent commands being generated in response to the same event.According to some embodiments, the trained machine learning model 295may be trained by updating a natural language processing device databasewith communications from customers that have been labeled using, forexample, a web user interface. Such data in the natural languageprocessing device database may undergo supervised training in a neuralnetwork model using a neural network training algorithm while the modelis offline before being deployed in the system 100.

According to some embodiments, a NLP model of the system 100 may utilizedeep learning models such as convolutional neural network (CNN) thattransforms a word into a word vector and long short-term memory (LSTM)that transforms a sequence of word vectors into intent. The NLP modelmay also be trained to recognize named entities in addition to intents.For example, a named entity may include persons, places, organizations,account types, and product types. According to some embodiments, whenthe dialogue management device 122 generates a command, such as a firstcommand, it may determine an entity that will execute the command, suchas, for example, the API server 126, the NLP device 124, a communicationinterface 301, or some other device or component, such that only thedetermined type of entity may pull the command from the command queue270. For example, in the embodiment shown in FIG. 3, the dialoguemanagement device 122 may determine that the first command is to beexecuted by the NLP device 124 to determine the meaning of the incomingcustomer dialogue message. According to some embodiments, at the timethe dialogue management device 122 creates a new command, the dialoguemanagement device may also update the customer information database 280(and/or database 128) with information about a previous or concurrenttransaction or customer interaction.

In accordance with certain example implementations of the disclosedtechnology, and with continued reference to FIG. 3, the NLP device 124may receive the first command from the command queue 270, execute thecommand, and generate a second event to be placed in the event queue260. According to some embodiments, the NLP device 124 may continuouslyor intermittently monitor the command queue 270 to detect new commandsand upon detecting a new command, may receive the command from thecommand queue 270. Upon receiving a command, the NLP device 124 mayperform various functions depending on the nature of the command. Forexample, in some cases, the NLP device 124 may determine the meaning ofan incoming dialogue message in response to executing the command.According to some embodiments, the NLP device 124 may determine themeaning of an incoming dialogue message by utilizing one or more of thefollowing artificial intelligence techniques: intent classification,named entity recognition, sentiment analysis, relation extraction,semantic role labeling, question analysis, rule extraction anddiscovery, and story understanding. Intent classification may includemapping text, audio, video, and/or or other media into an intent chosenfrom a set of intents, which represent what a customer is stating,requesting, commanding, asking, or promising, in an incoming customerdialogue message. Intent classifications may include, for example, arequest for an account balance, a request to activate a credit/debitcard, an indication of satisfaction, a request to transfer funds, or anyother intent a customer may have in communicating a message. Namedentity recognition may involve identifying named entities such aspersons, places, organizations, account types, and product types intext, audio, video, or other media. Sentiment analysis may involvemapping text, audio, video, or other media into an emotion chosen from aset of emotions. For example, a set of emotions may include positive,negative, anger, anticipation, disgust, distrust, fear, happiness, joy,sadness, surprise, and/or trust. Relation extraction may involveidentifying relations between one or more named entities in text, audio,video, or other media. A relation may be for example, a “customer of”relation that indicates that a person is a customer of an organization.Semantic role labeling may involve identifying predicates along withroles that participants play in text, audio, video, or other media. Anexample of semantic role labeling may be identifying (1) the predicateEat, (2) Tim, who plays the role of Agent, and (3) orange, which playsthe role of Patient, in the sentence “Tim ate the orange.” Questionanalysis may involve performing natural language analysis on a question,including syntactic parsing, intent classification, semantic rolelabeling, relation extraction, information extraction, classifying thetype of question, and identifying what type of entity is beingrequested. Rule extraction and discovery may involve extracting generalinference rules in text, audio, video, or other media. An example ofrule extraction may be extracting the rule that “When a person turns ona light, the light will light up” from “Matt turned on the light, but itdidn't light up.” Story understanding may involve taking a story andidentifying story elements including (1) events, processes, and states,(2) goals, plans, intentions, needs, emotions, and moods of the speakerand characters in the story, (3) situations and scripts, and (4) themes,morals, and the point of the story.

In some cases, the NLP device 124 may perform natural languagegeneration in response to receiving a command. According to someembodiments, the NLP device 124 may perform natural language generationby utilizing one or more of the following artificial intelligencetechniques: content determination, discourse structuring, referringexpression generation, lexicalization, linguistic realization,explanation generation. Content determination may involve deciding whatcontent to present to the customer out of all the content that might berelevant. Discourse structuring may involve determining the order andlevel of detail in which content is expressed. Referring expressiongeneration may involve generating expressions that refer to entitiespreviously mentioned in a dialogue. Lexicalization may involve decidingwhat words and phrases to use to express a concept. Linguisticrealization may involve determining what linguistic structures, such asgrammatical constructions, to use to express an idea. Explanationgeneration may involve generating a humanly-understandable, transparentexplanation of a conclusion, chain of reasoning, or result of a machinelearning model. In the example embodiment shown in FIG. 3, the NLPdevice 124 may determine the meaning of the incoming customer dialoguemessage and may convert it to a form that can be processed by thedialogue management device 122. Accordingly, the second event generatedby the NLP device 124 may represent a determined meaning of the incomingcustomer dialogue message and the NLP device 124 may send the secondevent to the event queue 260.

In accordance with certain example implementations of the disclosedtechnology, the dialogue management device 122 may receive the secondevent from the event queue 260. In some embodiments, the dialoguemanagement device 122 may also update the customer context by receivingupdated customer information. In response to processing the secondevent, the dialogue management device 122 may generate a second commandto be placed in a command queue 270. According to some embodiments,dialogue management device 122 may generate the second command based onthe processed event, the customer context, and/or the customerinformation using one or more of a rules-based platform 290 and atrained machine learning model 295 as described above with respect toFIG. 2.

In the example embodiment shown in FIG. 3, the second event mayrepresent a customer's request to know, for example, their accountbalance. Based on the customer context, customer information,rules-based platform 290 and/or trained machine learning model 295, thedialogue management device 122 may decide, for example, using predictiveanalytics that it has enough information to create a second event thatrepresents instructions to an API associated with the API server 126 tolook up the customer's account balance. However, in some embodiments,the dialogue management device 122 may decide that, for example, it istoo uncertain as to which account the customer is seeking informationabout and may instead create a second event that represents instructionsto the communication interface 301 to send a message to the user device102 requesting more information. Accordingly, based on the customercontext, the rules-based platform 290, and the trained machine learningmodel 295, the dialogue management device 122 may change or adapt itsresponses to a given request over time.

In accordance with certain example implementations of the disclosedtechnology, the API server 126 may receive the second command fromcommand queue 270, execute the command, and generate a third event to beplaced in event queue 260. According to some embodiments, the API server126 may continuously or intermittently monitor the command queue 270 todetect new commands and, upon detecting a new command, may receive thecommand from the command queue 270. Upon receiving a command, the APIserver 122 may perform various functions depending on the nature of thecommand. For example, in some cases, the API server 122 call up an APIstored locally or remotely on another device, to retrieve customer data(e.g., retrieve an account balance), perform an account action (e.g.,make a payment on a customer account), authenticate a customer (e.g.,verify customer credentials), check a status of a revocable token,and/or execute an opt-in/opt-out command (e.g., change account to opt-into paperless notifications, opt-in or opt-out of account servicing bySMS texting, etc.). Accordingly, in some embodiments, the third eventmay represent, for example, a retrieved account balance, anacknowledgement of the performance of an account action, anacknowledgement of the execution of an opt-in/opt-out command, averification or denial of a customer's credentials, a revocation of atoken, etc.

In certain example implementations, the dialogue management device 122may receive the third event from the event queue 260 in response todetecting it as described above. In some embodiments, dialoguemanagement device 122 may also update the customer context by receivingupdated customer information. The dialogue management device 122 may, inresponse to processing the third event, generate a third command to beplaced in command queue 270. According to some embodiments, dialoguemanagement device 122 may generate the third command based on theprocessed third event, the customer context, and/or customer informationusing one or more of rules-based platform 290 and trained machinelearning model 295 in a fashion similar to the generation of the firstcommand described above. In some embodiments, dialogue management device122 may also generate a response dialogue message in response toprocessing an event, such as the third event. In some embodiments,dialogue management device 122 may receive a response dialogue messageas an event produced by NLP device 124. According to some embodiments,the third command may represent a command or instruction tocommunication interface 301 to transmit the response dialogue messageto, for example, user device 102.

In certain example implementations, the communication interface 301 mayreceive and execute the third command, which may cause the communicationinterface 301 to transmit (e.g., via SMS) the response dialogue messageto user device 102. In some embodiments, the communication interface 301may continuously or intermittently monitor the command queue 270 for newcommands and may receive the third command in response to detecting thethird command in command queue 270. According to some embodiments, thecommunication interface 301 may be a standalone device having some orall of the elements of dialogue management device 122 as shown in FIG.2. In some embodiments, communication interface 301 may be integratedinto dialogue management device 122. In some embodiments, thecommunication interface 301 may be integrated into or associated withanother device of the system 100, such as, for example, the API gateway110, the local network 114, the web server 130, the API server 126, orthe NLP server. In accordance with certain example implementations ofthe disclosed technology, (and as will be discussed further withreference to FIG. 4) the communication interface 301 may be configuredto send “contact card” information (in the form of a SMS message, forexample) to the user device 102 upon authentication and enrollment inthe SMS account servicing. For example, the “contact card” informationmay provide a convenient way for the user device 102 to receive andstore (for example, in the user's contacts) the SMS number associatedwith the intelligent assistant system.

As discussed with respect to FIGS. 1-3, the system 100 may enableautomating natural language dialogue with a customer by utilizing thestructure provided by the event queue 260, dialogue management device122, command queue 270, API server 126, NLP server 124, andcommunication interface 301 to adaptively respond to customer messages.Certain example implementations of the disclosed technology may leverageartificial intelligence in the machine learning models and naturallanguage processing device to adaptively respond to customercommunications using natural language. In certain exampleimplementations, the use of a repeatedly updating customer context andinformation may enable the system 100 to generate and provide customizedresponses to individual customers and adapt the responses over time. Byutilizing artificial intelligence and machine-learning by the NLP device124, and a by repeatedly updating customer context/informationmaintained by the dialogue management device 122, the system may enablethe non-deterministic, adaptive, and customized conversational responsesto customer dialogue messages. Further, according to some embodiments,the system 100 may enable asynchronous processing of events and creationof commands by the dialogue management device 122. Further, while FIG. 3and the related description appear to show a particular single cycle ofevents, it should be appreciated that multiple different cycles ofevents may be processed in parallel by the dialogue management device122.

In some embodiments, the trained machine learning model 295 (asdiscussed with reference to FIG. 2) may include a people model thatserves to estimate a customer's mindset per use case, and over time. Forexample, the people model may estimate how stressed out a customer isand determine, for example, how fast they want to conduct a transactionor interaction. The trained machine learning model 295 may include, forexample, a relevance measure that may quantitatively assess how relevanta particular conversion with a customer is based on the percent of taskcompletion and rate of return conversations. The trained machinelearning model 295 may include an affect recognition functionality thatseeks to recognize a customer's emotions based on facial expressions,audio speech signals, images, gestures, blood pressure, heart rate, orother such customer data that may be collected by a user device 102 andtransmitted to the system 100. In some embodiments, the trained machinelearning model 295 may include payment and financial planning featuresthat model risk factors, savings, and spending patterns over time. Insome embodiments, the trained machine learning module 295 may includeobservations of the accuracy and effectiveness of the automated naturallanguage interactions by tracking business metrics over time, such asfor example, a reduction in call center volume over a period of time. Insome embodiments, the trained machine learning module 295 may enable theexecution of hypothesis-driven micro-experiments that enable the systemto test a model hypothesis on a small population of users to validatewhether the hypotheses are valid or not.

In some embodiments, the system 100 architecture may allow the APIserver 126, the NLP device 124, and the communication interface 301 tooperate independently from one another by separately pulling commandsfrom command queue 270. In certain example implementations, the system100 may provide the advantage of asynchronous operations. Accordingly,the entire system may be stateless, with no side effects to calling aparticular function.

FIG. 4 is an example system functionality diagram of a process 400 forcontrolling enrollment and secure persistent account servicingcommunications via SMS texting. In accordance with certain exampleimplementations of the disclosed technology, the process 400 may beexecuted using the dialogue management device 122 in concert with one ormore of the system 100 components (discussed with respect to FIGS. 1-3)to map user generated text to specific account servicing functions,including retrieval of account information, transactions, and status,and account servicing actions, including transactions, transfers,updates, and preferences. According to an example implementation of thedisclosed technology, the dialogue management device 122 of the system100 manages the dialogue state and the interaction with the user toaccomplish the account servicing intent by interpreting the accountcontext and using one or more rounds of dialogue to solicit additioninformation from the user and to disambiguate the account servicingintent. In an example implementation, the system 100 then uses thenatural language processing device 124 to produce the text response tothe users account servicing request, which is delivered via SMS text.Accordingly, the access to account servicing functions via the system100 may be determined by one or more components 110-130 of the system100 for controlling enrollment and secure persistent SMS texting accountservicing communications.

The process 400 may enable customers to access account informationand/or perform account servicing functions by texting with theintelligent assistant without having to login to a website or mobile appevery time. Certain example implementations of the disclosed technologymay provide an improved experience for a customer, by enabling accountservicing through digital self-service channels without the friction ofa customer having to navigate to a website or mobile app and/or providelogin credentials each time the customer interacts with the system 100.The example implementations may provide functionality that enables acustomer to select an identifier of the intelligent assistant from alisting of contacts, or from a recent conversation etc., and initiateaccount servicing dialogue with the intelligent assistant via SMS, justas the customer may initiate an SMS dialogue with any other contact.

According to an example implementation of the disclosed technology, andas depicted in block 402, the process 400 may utilize website enrollment(and/or enrollment through a mobile app), in which customers mayauthorize (and/or be authorized) to establish persistent secure accessto account servicing via SMS text based on an initial (one-time) loginand authorization process. In certain example implementations of thedisclosed technology, a customer may perform the initial login in to thewebsite or mobile app by supplying authentication credentials (such as acode, two-factor authorization, biometric information, etc.). Onceauthenticated, a customer may be granted persistent SMS access byproviding additional information, including (but not limited to) theirmobile phone number, consent to communicate with the account providervia SMS text, and consent to service their account via SMS text. Asdiscussed above with reference to FIG. 1, and according to certainexample implementations, once authorized and enrolled via the websiteenrollment, a revocable token associated with the user's account may begenerated and stored in the enrollment token store 118. Additionaldetails regarding the revocable token will be discussed below withrespect to the method flow diagram of FIG. 5. As discussed above withreference to FIG. 3, and according to certain example implementations,once authorized and enrolled via the website enrollment, a “contactcard” (or similar identifying information) may be sent the user's mobiledevice as a convenient way for the user to add a contact entry to theirmobile device for SMS messaging communications with the intelligentassistant system 100.

In block 404, a message, such as a SMS text, from a customer andoriginating from a mobile device, such as user device 102 as shown inFIG. 1, may be received by the system 100. In accordance with certainexample implementations of the disclosed technology, SMS messaginginteractions between the user device 102 and the system 100 may commenceat any point in time (i.e., days or weeks) after the website enrollmentprocess (barring a timeout or revocation of a token) and may span over aplurality of interactions. In certain instances, the interactions can beintermittent. Accordingly, once authenticated and enrolled, all thecustomer needs to do is open their traditional SMS messaging app tointeract with the intelligent assistant system 100, for example, in thesame way they communicate via SMS messages to friends. In block 406, aphone number of mobile device may be extracted from the received messageand utilized to determine whether the customer account associated withthe phone number is authorized to utilize the account servicing via SMStexting. This step may be performed by the phone number authenticationmodule 116 of FIG. 1. In some examples, phone number authenticationmodule 116 may attempt to retrieve data from the phone number store,such as phone number data store 120 of FIG. 1 (as shown in block 410).

In accordance with certain example implementations of the disclosedtechnology, if the phone number extracted from the message does notmatch with any currently stored phone numbers in the phone number datastore 120, the phone number authentication step 406 may direct thecustomer back to the website enrollment 402 for authentication, asdiscussed above. As depicted in block 408, if the phone number extractedfrom the message matches with a currently stored phone number in thephone number data store 120, the phone number authentication step maycheck if there is an active (revocable) token in the enrollment tokenstore 118 that authorizes the customer's interaction with theintelligent assistant via SMS text. If the token associated with thephone number does not exist, or if it has been revoked, the phone numberauthentication step 406 may direct the customer back to the websiteenrollment 402 to generate or renew the token. In accordance withcertain example implementations of the disclosed technology, the system100 may allow SMS account servicing on the conditions that: (1) thephone number extracted from the incoming message matches with a phonenumber in the phone number data store 120; and that (2) an active,authorized token associated with the phone number exists in theenrollment token store 118. In certain example implementations, thetoken may be checked per block 408 before the phone number is checkedper block 410.

In accordance with certain example implementations of the disclosedtechnology, and as depicted in block 424, the SMS enrollment token maybe revoked when any of the following occurs: the customer changes theirmobile number; the customer revokes consent to communicate via SMS text(for example, by texting “STOP” to the system 100); the customer revokesconsent to service their account via SMS text (for example, by texting“UNENROLL” to the system 100, which may be interpreted by the naturallanguage processor as intent to revoke consent); and/or the customer'smobile number appears on a list of mobile numbers that have switchedcarriers. In accordance with certain example implementations of thedisclosed technology, a mobile number that has been assigned to a newcarrier may be detected by an automated process that checks thecustomer's mobile number against a mobile number feed provided bywireless carriers. In certain example implementations, the system 100may utilize a third-party service to verify a customer's phone numberchange by a carrier (or between carriers) for continuity with othercustomer information (such as an address), for example, to avoid tokenrevocation when the customer changes their phone number. As depicted byblock 426, the SMS enrollment token may expire (or be revoked) if thecustomer does not service their account via SMS text for apre-determined number of days (such as 60 days, 120 days, or any perioddetermined by the account provider). Accordingly, the system 100 maykeep track of the last time the account has been accessed by SMSmessaging. In accordance with certain example implementations of thedisclosed technology, the revocable token may include a predefinedexpiration period. Provided that the SMS enrollment token has not beenrevoked or expired, the system 100 may allow the customer persistentaccess to the intelligent assistant for account servicing over multipletexting sessions without having to re-enroll or authenticate via thewebsite or mobile application.

As depicted in block 414, once a phone number and token associated withan incoming SMS text message has been authenticated, the system 100 mayproceed with a SMS chat session, allowing the customer to interact withthe system 100 for various account servicing functions. Responsive to areceived SMS message, system 100 may generate one or more SMS responsedialogue messages that may be transmitted for display at a user device102. According to an example implementation of the disclosed technology,the chat session 414 may utilize customer context 416 and naturallanguage processing 418 to produce dialogue 420 for SMS communicationwith mobile device associated with the authorized phone number. Incertain example implementations, the chat session 414, customer context416, natural language processing 418, and/or the generated dialogue 420may be processed by the dialogue management device 122 and/or theassociated components as discussed above with reference to FIGS. 1-3.

As depicted in block 422, (and as discussed above with respect to theenrollment token in block 408) a customer may terminate persistentauthentication for interaction with the intelligent assistant, forexample, by revoking consent to communicate and/or service their accountvia SMS text. In certain example implementations, after a mobileterminated intelligent assistant response 422 is received (or for anyrevocation of the token or lack of a match of the phone number),subsequent SMS messages received by the system may result in a “stock”message being delivered back to the originating mobile device to directthe customer back to the enrollment process as discussed above withreference to block 402.

FIG. 5 is a flowchart of a method 500 for enrollment and securepersistent SMS texting account servicing communications. In certainexample implementations, one or more of the steps of the method 500 maybe performed by dialogue management device 122 using processor 210 toexecute memory 230. In some embodiments, steps of method 500 may bedelegated to other components, such as the user device 102, and/orcomponents associated with the system 100. Following method 500, thesystem 100 may generate a response dialogue message that may betransmitted for display at, for example, user device 102.

In block 502, the method 500 includes receiving, at an enrollment webportal, enrollment data comprising: enrollment credentials identifying auser for authentication; a phone number of a mobile device associatedwith the user; and consent by the user to persistently interact with anaccount servicing system via SMS texting. In block 504, the method 500includes processing the received enrollment data. In block 506, themethod 500 includes authenticating the user responsive to processing thereceived enrollment data. In block 508, the method includes storing, ina phone number data storage, the phone number of the mobile deviceassociated with the user. In block 510, the method 500 includesgenerating, responsive to the authenticating, a revocable token forpersistent access to a natural dialog module via a SMS texting gatewayfor the mobile device identified by the phone number.

Certain example implementations of the disclosed technology can includeinitiating a persistent SMS texting session with the mobile deviceidentified by the phone number and based on the revocable token.

In an example implementation, the persistent SMS texting session may beinitiated responsive to a match of the phone number stored in the phonenumber data storage.

Certain example implementations may include revoking the token to stopaccess to the natural dialogue module via the SMS texting gateway by themobile device identified by the phone number responsive to one or moreof: a detected change in the phone number, revocation of consent by theuser, a “STOP” or “UNENROLL” (or similar) text message received from themobile device, a disconnect indication received from a carrierassociated with the phone number, and a predetermined period ofinactivity.

Certain example implementations can include retrieving and interpretinguser generated text based on context associated with the user. Certainexample implementations can include generating response dialogue textbased on the interpreted user generated text and context associated withthe user. In certain example implementations, the context may be derivedfrom user information stored in a database, the user information caninclude one or more of: account types, account statuses, transactionhistory, conversation history, people models, an estimate of customersentiment, customer goals, and customer social media information.

Certain example implementations of the disclosed technology can includedetermining a meaning of the user generated text by utilizing one ormore of the following artificial intelligence techniques: intentclassification, named entity recognition, sentiment analysis, relationextraction, semantic role labeling, question analysis, rule extractionand discovery, and story understanding.

In an example implementation, the response dialogue text may begenerated by utilizing one or more of the following artificialintelligence techniques: content determination, discourse structuring,referring expression generation, lexicalization, linguistic realization,explanation generation.

Certain example implementations can include revoking the token to stopaccess to the natural dialogue module via the SMS texting gateway by themobile device identified by the phone number responsive to receiving, atthe enrollment web portal, one or more of: a change to the phone number,and a revoked consent to communicate with the account provider via SMStext.

Certain example implementations of the disclosed technology include asystem having one or more processors configured to initiate, responsiveto the authentication, a persistent SMS texting session with the mobiledevice identified by the phone number. In an example implementation, thepersistent SMS texting session is initiated responsive to: averification of an active token associated with the enrollment data; anda match of the phone number stored in the phone number data storage. Theone or more processors are further configured to retrieve accountcontext for the user identified by the phone number responsive to theauthentication.

In certain example implementations, the one or more processors arefurther configured to revoke the token to stop access to the naturaldialogue module via the SMS texting gateway by the mobile deviceidentified by the phone number responsive to one or more of: a detectedchange in the phone number, revocation of consent by the user, a “STOP”or “UNENROLL” (or similar) text message received from the mobile device,a disconnect indication received from a carrier associated with thephone number, and a predetermined period of inactivity.

In an example implementation, the system can include a natural languagedialogue module that can include a trained machine learning dialoguemanagement device configured to retrieve and interpret user generatedtext based on context associated with the user. In certain exampleimplementations, the dialogue management device may be furtherconfigured to generate response dialogue text based on the interpreteduser generated text and context associated with the user.

In certain example implementations, the one or more processors arefurther configured to revoke the token to stop access to the naturaldialogue module via the SMS texting gateway by the mobile deviceidentified by the phone number responsive to receiving, at theenrollment web portal, a change to the phone number.

As used in this application, the terms “component,” “module,” “system,”“server,” “processor,” “memory,” and the like are intended to includeone or more computer-related units, such as but not limited to hardware,firmware, a combination of hardware and software, software, or softwarein execution. For example, a component may be, but is not limited tobeing, a process running on a processor, an object, an executable, athread of execution, a program, and/or a computer. By way ofillustration, both an application running on a computing device and thecomputing device can be a component. One or more components can residewithin a process and/or thread of execution and a component may belocalized on one computer and/or distributed between two or morecomputers. In addition, these components can execute from variouscomputer readable media having various data structures stored thereon.The components may communicate by way of local and/or remote processessuch as in accordance with a signal having one or more data packets,such as data from one component interacting with another component in alocal system, distributed system, and/or across a network such as theInternet with other systems by way of the signal.

Certain embodiments and implementations of the disclosed technology aredescribed above with reference to block and flow diagrams of systems andmethods and/or computer program products according to exampleembodiments or implementations of the disclosed technology. It will beunderstood that one or more blocks of the block diagrams and flowdiagrams, and combinations of blocks in the block diagrams and flowdiagrams, respectively, can be implemented by computer-executableprogram instructions. Likewise, some blocks of the block diagrams andflow diagrams may not necessarily need to be performed in the orderpresented, may be repeated, or may not necessarily need to be performedat all, according to some embodiments or implementations of thedisclosed technology.

These computer-executable program instructions may be loaded onto ageneral-purpose computer, a special-purpose computer, a processor, orother programmable data processing apparatus to produce a particularmachine, such that the instructions that execute on the computer,processor, or other programmable data processing apparatus create meansfor implementing one or more functions specified in the flow diagramblock or blocks. These computer program instructions may also be storedin a computer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meansthat implement one or more functions specified in the flow diagram blockor blocks.

As an example, embodiments or implementations of the disclosedtechnology may provide for a computer program product, including acomputer-usable medium having a computer-readable program code orprogram instructions embodied therein, said computer-readable programcode adapted to be executed to implement one or more functions specifiedin the flow diagram block or blocks. Likewise, the computer programinstructions may be loaded onto a computer or other programmable dataprocessing apparatus to cause a series of operational elements or stepsto be performed on the computer or other programmable apparatus toproduce a computer-implemented process such that the instructions thatexecute on the computer or other programmable apparatus provide elementsor steps for implementing the functions specified in the flow diagramblock or blocks.

Accordingly, the block diagrams and flow diagrams support combinationsof means for performing the specified functions, combinations ofelements or steps for performing the specified functions, and programinstruction means for performing the specified functions. It will alsobe understood that each block of the block diagrams and flow diagrams,and combinations of blocks in the block diagrams and flow diagrams, canbe implemented by special-purpose, hardware-based computer systems thatperform the specified functions, elements or steps, or combinations ofspecial-purpose hardware and computer instructions.

Certain implementations of the disclosed technology are described abovewith reference to user devices may include mobile computing devices.Those skilled in the art recognize that there are several categories ofmobile devices, generally known as portable computing devices that canrun on batteries but are not usually classified as laptops. For example,mobile devices can include, but are not limited to portable computers,tablet PCs, internet tablets, PDAs, ultra-mobile PCs (UMPCs), wearabledevices, and smart phones. Additionally, implementations of thedisclosed technology can be utilized with internet of things (IoT)devices, smart televisions and media devices, appliances, automobiles,toys, and voice command devices, along with peripherals that interfacewith these devices.

In this description, numerous specific details have been set forth. Itis to be understood, however, that implementations of the disclosedtechnology may be practiced without these specific details. In otherinstances, well-known methods, structures and techniques have not beenshown in detail in order not to obscure an understanding of thisdescription. References to “one embodiment,” “an embodiment,” “someembodiments,” “example embodiment,” “various embodiments,” “oneimplementation,” “an implementation,” “example implementation,” “variousimplementations,” “some implementations,” etc., indicate that theimplementation(s) of the disclosed technology so described may include aparticular feature, structure, or characteristic, but not everyimplementation necessarily includes the particular feature, structure,or characteristic. Further, repeated use of the phrase “in oneimplementation” does not necessarily refer to the same implementation,although it may.

Throughout the specification and the claims, the following terms take atleast the meanings explicitly associated herein, unless the contextclearly dictates otherwise. The term “connected” means that onefunction, feature, structure, or characteristic is directly joined to orin communication with another function, feature, structure, orcharacteristic. The term “coupled” means that one function, feature,structure, or characteristic is directly or indirectly joined to or incommunication with another function, feature, structure, orcharacteristic. The term “or” is intended to mean an inclusive “or.”Further, the terms “a,” “an,” and “the” are intended to mean one or moreunless specified otherwise or clear from the context to be directed to asingular form. By “comprising” or “containing” or “including” is meantthat at least the named element, or method step is present in article ormethod, but does not exclude the presence of other elements or methodsteps, even if the other such elements or method steps have the samefunction as what is named.

While certain embodiments of this disclosure have been described inconnection with what is presently considered to be the most practicaland various embodiments, it is to be understood that this disclosure isnot to be limited to the disclosed embodiments, but on the contrary, isintended to cover various modifications and equivalent arrangementsincluded within the scope of the appended claims. Although specificterms are employed herein, they are used in a generic and descriptivesense only and not for purposes of limitation.

This written description uses examples to disclose certain embodimentsof the technology and also to enable any person skilled in the art topractice certain embodiments of this technology, including making andusing any apparatuses or systems and performing any incorporatedmethods. The patentable scope of certain embodiments of the technologyis defined in the claims, and may include other examples that occur tothose skilled in the art. Such other examples are intended to be withinthe scope of the claims if they have structural elements that do notdiffer from the literal language of the claims, or if they includeequivalent structural elements with insubstantial differences from theliteral language of the claims.

Use Case Examples

The following example use cases are intended solely for explanatorypurposes, without limiting the scope of the disclosed technology.

In an example use case, a customer may have a question or requestassociated with an account they have with an organization. For example,the customer may want to know information related their account, such asthe account balance, due date for payment, specifics about a purchase,etc. In some instances, the customer may want to perform an actionrelated to their account, such as making a payment, dispute a charge,etc. In these use cases, the customer may further wish to have aconvenient and efficient way to pose their question or request accountservice without having to deal with the waiting times, inefficienciesand complexities that are often associated with customer serviceinteractions involving call centers or interactive voice responsesystems. In this use case, the customer may prefer using text-basedmessaging as a preferred form of communication for posing questions orrequesting service associated with their account.

To allow access to the system using SMS texting interactions, thecustomer will login in to the website or mobile app associated with theorganization by supplying authentication credentials (such as a code,two-factor authorization, biometric information, etc.). Onceauthenticated, the customer may be granted persistent SMS access byproviding additional information, including (but not limited to) theirmobile phone number, consent to communicate with the organization viaSMS text, and consent to service their account via SMS text. Onceproperly authenticated, the customer may then use their mobile device toaccess account information and/or perform account servicing functions bytexting with the intelligent assistant without having to login to awebsite or mobile app every session. This process may provide animproved experience for a customer, by enabling account servicingthrough digital self-service channels without the friction of a customerhaving to navigate to a website or mobile app and/or provide logincredentials each time there is an interaction with the system.

In this (and other) use cases, the disclosed technology provides asecure and persistent authentication process for accessing accountservicing functions via SMS texting by utilizing a revocable token,which may be utilized to secure and protect access to sensitiveinformation. For example, the customer's mobile phone number and theconsent to communicate with the organization via SMS text may bepersisted in a data store, which can only be changed while the customeris logged in. In certain example implementations, the revocable tokenmay be based on the association of the customer's mobile phone numberwith their digital profile identification. In an example implementation,each time a customer interacts with the intelligent assistant via SMStext, the system checks the data store to verify that the customer stillhas the same mobile phone number and has not revoked consent tocommunicate via SMS text. The token is also checked to see if it isstill valid. If the token has expired, customers must log in to thewebsite or mobile app again to re-establish the persistentauthentication token for account servicing via SMS text.

In accordance with certain example implementations of the disclosedtechnology, the token may expire when any of the following occurs: thecustomer changes their mobile number; the customer revokes consent tocommunicate via SMS text; the customer revokes consent to service theiraccount via SMS text; the customer does not service their account viaSMS text for a pre-determined number of days; and/or the customer'smobile number appears on a list of mobile numbers that have switchedcarriers.

In another example use case, once the customer has performed the initialauthentication and consent process via the website or mobile app, thecustomer may send a text message from their (authorized) mobile deviceto a number provided by the system (and associated with theorganization). For example, the SMS message may be: “Hello, can youplease tell me my account balance?” The SMS text message may be receivedby the system (e.g., via the SMS aggregator 104). The system may firstcheck to see if the mobile device number associated with the SMS messageis associated with and account on the system, and to also check if thereis a valid token associated with the phone number. If so, the system mayproceed to process the message to understand its meaning and determine aresponse. In the process of making the determination about how torespond, the system may consider the customer context of the user. Forexample, the system may analyze the currently known data about thecustomer, such as the customer's account information, previousinteractions with the customer, the customer's goals, the customer'ssocial media presence, and an estimation of the customer's emotionalstate to determine how to respond. In doing so, the system may decide,based on previous requests, that the customer is requesting informationabout a checking account, and therefore may decide to respond with thecustomer's checking account information. In another instance, the systemmay decide that it does not have enough information to determine whichaccount the customer is referring to and may send a SMS message to thecustomer requesting more information. Further, the system may customizethe form of the response.

Another use case involves the system proactively providing a customerwith unrequested information via SMS during a customer-initiated sessionand based on a predictive analysis of the customer's needs. Suchpredictive analysis can be conducted using machine learning and modelingin conjunction with knowledge of the customer context. For example, acustomer may send the system a SMS message requesting a change inautomatic bill payments. In addition to making the requested change, thesystem may send a SMS message to the customer to remind them that theyhave a bill coming due soon, despite the fact that the customer did notrequest that information. In this way, the system can take proactivesteps to meet a customer's needs.

1. A computer-implemented method, comprising: receiving a request toservice an account associated with an authenticated user of a mobiledevice, the account servicing to be performed via a natural languagedialogue module; and responsive to the request: performing a predictiveanalysis of the user's needs; generating, with the natural languagedialogue module, response dialogue text comprising unrequestedinformation based on the predictive analysis of the user's needs; andsending, to the mobile device, the response dialogue text.
 2. The methodof claim 1, wherein performing the predictive analysis of the user'sneeds is based on user-generated text received as part of the request.3. The method of claim 1, wherein performing the predictive analysis ofthe user's needs is based on knowledge of the user's context, whereinthe user's context is derived from user information stored in adatabase, the user information comprising one or more of: account types,account statuses, transaction history, conversation history, peoplemodels, an estimate of customer sentiment, customer goals, and customersocial media information.
 4. The method of claim 1, wherein performingthe predictive analysis is conducted using machine learning andmodeling.
 5. The method of claim 1, wherein the request is initiatedbased on a selection, by the authenticated user, of an identifier on themobile device corresponding to an intelligent assistant associated withthe natural language dialogue module.
 6. The method of claim 1, furthercomprising: interpreting, with the natural language dialogue module,context associated with the user; and generating, with the naturallanguage dialogue module, the response dialogue text based on thecontext associated with the user.
 7. The method of claim 1, furthercomprising authenticating the user responsive to one or more of arevocable token of non-expired status or a determined non-elapsed statusof a predetermined period since a previous servicing of the account viathe mobile device.
 8. The method of claim 7, further comprising revokingthe token to stop access to the natural language dialogue moduleresponsive to one or more of: a detected change in a phone number,revocation of consent by the user, a STOP message received from themobile device, a disconnect indication received from a carrierassociated with the mobile device, and a predetermined period ofinactivity.
 9. The method of claim 1, further comprising receiving adevice identifier associated with the mobile device and initiating anelectronic communication session with the mobile device identified bythe device identifier.
 10. The method of claim 1, further comprisingretrieving and interpreting user-generated text and interpreting anemotional state of the user based on the user-generated text and contextassociated with the user.
 11. The method of claim 1, further comprisingdetermining a meaning of user-generated text received as part of therequest by utilizing one or more of the following artificialintelligence techniques: intent classification, named entityrecognition, sentiment analysis, relation extraction, semantic rolelabeling, question analysis, rule extraction and discovery, and storyunderstanding, and wherein the response dialogue text is generated byutilizing one or more of the following artificial intelligencetechniques: content determination, discourse structuring, referringexpression generation, lexicalization, linguistic realization,explanation generation.
 12. The method of claim 1, wherein the responsedialogue text comprises a request for additional information from theuser.
 13. A system for secure persistent account servicingcommunications, the system comprising: one or more processors incommunication with: an intelligent assistant system that includes anatural language processing device; an information storage databasestoring a plurality of records associated with a plurality of mobiledevices; and memory in communication with the one or more processors andstoring instructions that, when executed by the one or more processors,are configured to cause the system to: receive a request to service anaccount associated with an authenticated user of a mobile device, theaccount servicing to be performed via the natural language processingdevice; and responsive to the request: perform a predictive analysis ofthe user's needs; generate, with the natural language processing device,response dialogue text comprising unrequested information based on thepredictive analysis of the user's needs; and send, to the mobile device,the response dialogue text.
 14. The system of claim 13, wherein theinstructions cause the system to perform the predictive analysis ofuser's needs based on user-generated text received as part of therequest.
 15. The system of claim 13, wherein the instructions cause thesystem to perform the predictive analysis of user's needs based onknowledge of the user's context, wherein the user's context is derivedfrom user information stored in the information storage database, theuser information comprising one or more of: account types, accountstatuses, transaction history, conversation history, people models, anestimate of customer sentiment, customer goals, and customer socialmedia information.
 16. The system of claim 13, wherein the instructionsfurther cause the system to receive the request based on a selection, bythe authenticated user, of an identifier on the mobile devicecorresponding to an intelligent assistant associated with the naturallanguage processing device.
 17. A non-transitory computer readablestorage medium storing instructions for use with one or more processorsin communication with: a natural language dialogue module; aninformation storage database storing a plurality of records associatedwith a plurality of mobile devices; and wherein the instructions areconfigured to cause the one or more processors to perform a methodcomprising: receiving a request to service an account associated with anauthenticated user of a mobile device, the account servicing to beperformed via a natural language dialogue module; and responsive to therequest: performing a predictive analysis of the user's needs;generating, with the natural language dialogue module, response dialoguetext comprising unrequested information based on the predictive analysisof the user's needs; and sending, to the mobile device, the responsedialogue text.
 18. The non-transitory computer readable storage mediumof claim 17, wherein performing the predictive analysis of the user'sneeds is based on user-generated text received as part of the request.19. The non-transitory computer readable storage medium of claim 17,wherein performing the predictive analysis of the user's needs is basedon knowledge of the user's context, wherein the user's context isderived from user information stored in a database, the user informationcomprising one or more of: account types, account statuses, transactionhistory, conversation history, people models, an estimate of customersentiment, customer goals, and customer social media information. 20.The non-transitory computer readable storage medium of claim 17, whereinthe instructions are further configured to cause the one or moreprocessors to generate the request based on a selection, by theauthenticated user, of an identifier on the mobile device correspondingto an intelligent assistant associated with the natural languagedialogue module.